Control data driven modifications and generation of new schema during runtime operations

ABSTRACT

A computational device receives input data and control data, where the control data includes instructions to modify one or more operations performed during a runtime execution associated with the input data. The control data is processed to modify the one or more operations during the runtime execution associated of the input data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of application Ser. No. 13/801,556filed on Mar. 13, 2013, which is incorporated herein by reference in itsentirety.

BACKGROUND

1. Field

The disclosure relates to a method, system, and computer program productfor control data driven modifications and generation of new schemaduring runtime operations.

2. Background

An Extract, Transform and Load (ETL) job may be executed as a process toprocess data from various sources. During execution of the ETL job, datamay be extracted from input sources and transformed to fit operationalneeds. The transformed data may be loaded into a target, such as adatabase.

A schema refers to the structure of data described in a notation that issupported by a database management system, an application, or anindustry standard. For example, a schema may indicate the organizationof a table used to represent data.

A runtime environment may implement operations for the execution ofmachine instructions of applications written in a programming language.ETL jobs may execute in a runtime environment.

Mechanisms for processing different schemas and mixed data may includethe use of a graphical user interface to design one ETL job for eachschema. That is, at job design time users may be provided with schemasthat describe input and output data and may select from among theschemas for each ETL component for a job, so that at runtime the ETL jobprocesses input data based on the schemas that were provided to andselected by the user for the job design prior to runtime. Such anapproach may be applied for building data warehouse databases that aredefined by a number of database tables with static schemas.

SUMMARY OF THE PREFERRED EMBODIMENTS

Provided are a method, system, and computer program product in which acomputational device receives input data and control data, where thecontrol data includes instructions to modify one or more operationsperformed during a runtime execution associated with the input data. Thecontrol data is processed to modify the one or more operations duringthe runtime execution associated with the input data.

In further embodiments, the control data includes a schema, and theinput data is processed in accordance with the schema provided by theinput data.

In yet further embodiments, a determination is made that for at least aportion of the input data no corresponding schema to process the portionof the input data has been received. A new schema is generated toprocess the portion of the input data for which no corresponding schemahas been received.

In certain embodiments, the receiving and the processing is performed byan Extract Transform Load (ETL) component that executes in thecomputational device, where the ETL component extracts information fromthe input data and the control data, transforms the information inconformance with operational needs, and loads the transformedinformation to generate an output.

In additional embodiments, the control data provides a first instructionfor modifying a first operation to be performed during the runtimeexecution, and no instructions are provided for modifying a secondoperation to be performed during the runtime execution. A modificationis made to the first operation in accordance with the first instruction,during the runtime execution. The second operation is performed withoutany modification, during the runtime execution.

In certain embodiments, at least a plurality of data records in theinput data are structured hierarchically.

In further embodiments, at least one schema associated with the inputdata changes over time.

In yet further embodiments, data records of the input data are parsed inaccordance at least one schema and processed via an Extract TransformLoad (ETL) job.

BRIEF DESCRIPTION OF THE DRAWINGS

Referring now to the drawings in which like reference numbers representcorresponding parts throughout:

FIG. 1 illustrates a block diagram of a computing environment thatincludes a server computational device coupled to one or more clientcomputational devices, in accordance with certain embodiments;

FIG. 2 illustrates a block diagram that shows exemplary input datareceived by an exemplary operation of an ETL processor that executes inthe server computational device, in accordance with certain embodiments;

FIG. 3 illustrates a block diagram that shows exemplary control datawith one or more schemas and instructions received by an exemplaryoperation of the ETL processor that executes in the server computationaldevice, in accordance with certain embodiments;

FIG. 4 illustrates a block diagram that shows exemplary control datathat controls operations in a runtime environment, in accordance withcertain embodiments;

FIG. 5 illustrates a first flowchart that shows operations performed inthe server computational device, in accordance with certain embodiments;

FIG. 6 illustrates a second flowchart that shows operations performed inthe server computational device, in accordance with certain embodiments;and

FIG. 7 illustrates a block diagram of a computational system that showscertain elements that may be included in at least the servercomputational device that executes operations of the ETL processor, andthe client computational device of FIG. 1, in accordance with certainembodiments.

DETAILED DESCRIPTION

In the following description, reference is made to the accompanyingdrawings which form a part hereof and which illustrate severalembodiments. It is understood that other embodiments may be utilized andstructural and operational changes may be made.

Certain input sources for data may provide “mixed data” described bydifferent formats and schemas. For example a social network service mayprovide an input source that provides mixed data for an ETL job.Examples of data formats used by a social network service may includeextensible markup language (XML) and JavaScript* Object Notation (JSON).Some portions of the mixed data may be described by a schema, andwhereas some other portions, such as those provided in the JSON format,may not have any associated schema. *JavaScript is a trademark orregistered trademark of Oracle and/or its affiliates.

Extracting information from mixed data may require the creation ofmultiple ETL jobs. One ETL job may have to be targeted to one schema.Customers may have to create a plurality of ETL jobs, which may be timeconsuming. Furthermore, ETL jobs may not be able to handle dynamicallychanging data requirements, such as those seen in social networks. Ifcustomers change a schema, the ETL job created for the schema has to beupdated and recompiled. For the data without a schema, customers mayhave to provide a schema or a schema has to be generated from sampledata, such that the customer can create an ETL job to process the data.

A similar issue may arise in quality assurance. For a particular ETLjob, a quality assurance program may need to test the ETL job withvarious data described by different schemas, to make sure the ETL jobbehaves as expected. For different schemas, different ETL jobs have tobe designed to accomplish the perform testing tasks. If new designchanges are made, the quality assurance program may need to change manyETL jobs one at a time, which is very inefficient.

Certain embodiments provide a mechanism for creating an ETL processor(i.e., an ETL job) that can adjust to both schema changes and datachanges at runtime.

EMBODIMENTS

FIG. 1 illustrates a block diagram of a computing environment 100 thatincludes a server computational device 102 coupled to one or more clientcomputational devices 104, in accordance with certain embodiments.

The server computational device 102 and the client computational device104 may comprise any suitable computational device including thosepresently known in the art, such as, a personal computer, a workstation,a server, a mainframe, a hand held computer, a palm top computer, atelephony device, a network appliance, a blade computer, a storageserver, a database server, etc. In certain embodiments, the servercomputational device 102 and the client computational device 104 may becoupled via a network, such as the Internet, an intranet, a storage areanetwork, a local area network, etc. In other embodiments, the servercomputational device 102 and the client computational device 104 mayrefer to the same computational device.

The server computational device 102 includes an ETL processor 106 and aschema generator 108. The ETL processor 106 and the schema generator 108are applications that may be implemented in software, firmware, hardwareor any combination thereof.

The ETL processor 106 (i.e., an ETL job) may include many operations(i.e., steps), and exemplary operations 116 a, 116 b . . . 116 n of theETL processor as executed in a runtime environment 118 are shown inFIG. 1. Each operation of the ETL processor 106 receives inputs fromother operations or from the input data 110. Associated with eachoperation are one or more associated schemas that describe the inputsand outputs for the operation.

Exemplary operations 116 a, 116 b, . . . , 116 n of the ETL processor106 receive input data 110 and control data 112, from the clientcomputational device 104, for processing and generating an output 114,by transforming the input data 110. An exemplary operation of the ETLprocessor 106 (such as operation 116 a) may also be referred to as anETL component, where the ETL component extracts information from theinput data and the control data, transforms the information inconformance with operational needs, and loads the transformedinformation to generate an output.

The schema generator 108 included in the server computational device 102may generate a schema for a portion of the input data 110 for which theclient computational device 104 has not provided a schema. The schemasgenerated by the schema generator 108 may be used as a part of the inputschemas for operations 116 a, 116 b, . . . , 116 n.

FIG. 1 illustrates certain embodiments in which exemplary operations 116a, 116 b, . . . , 116 n of the ETL processor 106 process the input data110 based on information provided by the control data 112, where boththe input data 110 and the control data 112 are provided by the clientcomputational device 104. In certain embodiments, at least a pluralityof data records in the input data 100 are structured hierarchically. Infurther embodiments, at least one schema associated with the input data110 changes over time. In further embodiments, data records of the inputdata 110 are parsed by the exemplary operations 116 a, 116 b, . . . ,116 n of the ETL processor 106.

FIG. 2 illustrates a block diagram 200 that shows exemplary input data202 received by exemplary operations 116 a, 116 b, . . . , 116 n of theETL processor 106 executing in the server computational device 102, inaccordance with certain embodiments. The exemplary input data 202 may begenerated by the client computational device 104 and transmitted to theserver computational device 102.

In certain embodiments, the exemplary input data 202 may include aplurality of portions of data, and in FIG. 2, three exemplary portionsreferred to as portion A (reference numeral 204), portion B (referencenumeral 206), and portion C (reference numeral 208) have been shown. Forexample, portion A 204 may be the first ten thousand data records ofmixed data provided by a social network, portion B 206 may be the nexttwenty thousand data records of the mixed data provided by the socialnetwork, and portion C 208 may be next ten thousand data records of themixed data provided by the social network.

In certain embodiments, the client computational device 104 providesSchema X 210 to exemplary operations 116 a, 116 b, . . . , 116 n of theETL processor 106 for interpreting portion A 204 of the exemplary inputdata 202. The client computational device 104 provides Schema Y 212 tothe exemplary operations 116 a, 116 b, . . . , 116 n of the ETLprocessor 106 for interpreting portion B 206 of the exemplary input data202. However, the client computational device 104 does not provide anyschema to the exemplary operations 116 a, 116 b, . . . , 116 n of theETL processor 106 for interpreting portion C of the exemplary input data202. In such embodiments, the schema generator 108 is used to generatenew schemas for portion C 202 of the exemplary input data, and theexemplary operations 116 a, 116 b, . . . , 116 n of the ETL processor106 interprets portion C 208 in accordance with the new schemas. PortionA 204 and portion B 206 are interpreted in accordance with schema X 210and schema Y 212 respectively. Such schemas may be generated in manysituations, including situations in which the data stored in portion C208 is hierarchically arranged.

Therefore, FIG. 2 illustrates certain embodiments in which if a clientcomputational device does not provide a schema for a portion of theinput data 202, then a new schema is generated by using the schemagenerator 108 to interpret the portion of the input data 202 for whichno schema has been provided.

FIG. 3 illustrates a block diagram 300 that shows exemplary control data302 with one or more schemas 304 and instructions 306. The control data302 is sent associated with the input data 110, from the clientcomputational device 104 to the server computational device 102.

The instructions 306 include indications to modify exemplary operationsof the ETL processor 106 during runtime. The exemplary control data 302is received by the server computational device 102 from the clientcomputational device 104, and the exemplary operations 116 a . . . 116 nof the ETL processor 106 for processing the input data in the runtimeenvironment 118 may be altered based on the instructions 306 included inthe exemplary control data 302.

FIG. 4 illustrates a block diagram 400 that shows exemplary control data404 that controls operations in a runtime environment 406, in accordancewith certain embodiments (as shown via reference numeral 402).

Two exemplary operations, referred to as Operation A 408 and Operation B410 are shown in the exemplary runtime environment 406. The exemplarycontrol data 404 includes an instruction 412 to modify operation A 408in the runtime environment 406. As a result, operation A 408 is modifiedas per instruction 412 in the exemplary control data 404, and operationB 410 remains unmodified as no modification instruction for operation B410 is found in the control data 404.

FIG. 5 illustrates a first flowchart 500 that shows operations performedby the ETL processor 106 executing in the server computational device102, i.e., at runtime, in accordance with certain embodiments.

Control starts at block 502 in which an exemplary operation 116 areceives input data from other operations or as part of the input data110, and optional control data for the exemplary operation 116 a asdefined in the control data 112. The operation 116 a determines (atblock 504) whether control data for operation 116 a is present. If so(“yes” branch from block 504), then control proceeds to block 506 inwhich the runtime behavior is adjusted (at block 514) based on thecontrol data 112. Control proceeds to block 508 and the input data isprocessed in the runtime environment 118.

If at block 504 it is determined that control data is not present, thencontrol proceeds to block 510 (“no” branch from block 504) in which adetermination is made as to whether the input data refers to a schemafor a previously processed data record. If so, then the schema isavailable and the exemplary operation 116 a processes (at block 508) theinput data for the exemplary operation 116 a in accordance with theschema. If not (“no” branch from block 510), a determination is made (atblock 512) as to whether the input data for the exemplary operation 116a can be processed without generating a new schema. If so, then theinput data is processed (at block 508) with an earlier provided schema.

If at block 512 a determination is made that the input data for theexemplary operation 116 a cannot be processed without generating a newschema (“no” branch from block 512) control proceeds to block 514 atwhich a new schema is generated. Control proceeds to block 516 where theruntime behavior is adjusted based on the generated schema, and theinput data is processed (at block 508).

FIG. 6 illustrates a second flowchart 600 that shows operationsperformed in the server computational device 102, in accordance withcertain embodiments.

Control starts at block 602 in which an exemplary operation 116 a thatexecutes in the runtime environment of a computational device (e.g., theserver computational device 102) receives input data that may correspondto part of the input data 110. The exemplary operation 116 a may alsoreceive control data, where the control data may include instructions tomodify the exemplary operation 116 a during a runtime executionassociated with the input data 110. The control data is processed (atblock 604) to modify the exemplary operation 116 a during the runtimeexecution associated with the input data 110.

In certain embodiments, the control data includes a schema, and theinput data 110 is processed in accordance with the schema provided bythe input data.

From block 602, control may proceed in parallel with the execution ofblock 604 to block 606, where in block 606 a determination is made thatfor at least a portion of the input data 110 no corresponding schema toprocess the portion of the input data has been received. A new schema isgenerated (at block 608) to process the portion of the input data forwhich no corresponding schema has been received.

Therefore, FIGS. 1-6 illustrate certain embodiments in which controldata may be provided in association with input data to modify theoperations performed by an ETL processor during runtime. Additionally,each operation is able to generate a schema for an input data for theoperation, if the input data for the operation does not have anyassociated schema.

Further Embodiments

In an exemplary “parser job” comprising an XML parser that parses XMLdata based on the state machine generated from an XML schema, it may bedesirable for the XML parser to build a new state machine if itencounters a new schema, so that the XML parser may validate and processthe XML data against new schema. In this way, customers may need todesign one parser job to process the XML “mixed data” described bydifferent XML schemas.

Certain embodiments provide the ability to have a single ETL job thathandles mixed data with different schemas or no schema, versus themethod of creating one ETL job for each data type and schema. Time issaved for users by reducing the number of ETL jobs to be created andmaintained. In certain embodiments, a general template may be used todefine what can be dynamically set at runtime. For example, for the XMLparser, the parser can be dynamically configured with a different XMLschema at runtime. For the output step, the step can be dynamicallyconfigured with a different output schema, and so on. At runtime, inputdata is read from an input source. Optional control data that containsnew schemas and other configurable parameters and values to adjust theruntime behavior of each step in the job are made available. In thismanner, the schema is defined or adjusted from the incoming data. Wheneach step receives the input, the step adjusts itself based on thecontrol data for the step within the input as follows:

-   1. If there is no control data for the step and the real data refers    to a schema used in previous input, the step keeps the same runtime    behavior;-   2. If there is no control data for the step and the real data does    not refer to any schema, the step can either process the raw data    directly without using a schema or generate a schema from the data    before processing the real data;-   3. If there is control data for the step, the step adjusts itself    based on the new control data. In the XML parser case, the parser    will generate a new state machine based on the new XML schema to    validate and parse the incoming data. In the output step case, the    output step is reconfigured to extract the data fields defined by    the new output schema. A cache algorithm can be added to map the    control data to loadable software modules or packages so that the    step can switch between one behavior to another efficiently; and-   4. After the step processes the control data in a record, the step    process the real data in the record.

Referring to the examples above one application of certain embodimentsis to have one simple job design to process a stream of mixed data fromsocial networks defined by different schemas or by no schema. Thisresults in increased flexibility for ETL jobs in a social networkingenvironment. Jobs that may potentially cause an error with a data orformat change may now continue to function. Additionally, qualityassurance engineers may be able use one simple job to test varioustesting scenarios. Quality assurance engineers can focus on defining thetesting scenarios rather than spending time on using the product todesign jobs. This may result in a significant saving of time in thequality assurance process.

Additional Embodiment Details

The described operations may be implemented as a method, apparatus orcomputer program product using standard programming and/or engineeringtechniques to produce software, firmware, hardware, or any combinationthereof. Accordingly, aspects of the embodiments may take the form of anentirely hardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,aspects of the embodiments may take the form of a computer programproduct embodied in one or more computer readable medium(s) havingcomputer readable program code embodied there.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java*, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider). *Java is a trademark or registered trademark of Oracle and/orits affiliates.

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

FIG. 7 illustrates a block diagram that shows certain elements that maybe included in the server computational device 102, and the one or moreclient computational devices 104, in accordance with certainembodiments. The system 700 may comprise the server computational device102 and may include a circuitry 702 that may in certain embodimentsinclude at least a processor 704. The system 700 may also include amemory 706 (e.g., a volatile memory device), and storage 708. Thestorage 708 may include a non-volatile memory device (e.g., EEPROM, ROM,PROM, RAM, DRAM, SRAM, flash, firmware, programmable logic, etc.),magnetic disk drive, optical disk drive, tape drive, etc. The storage708 may comprise an internal storage device, an attached storage deviceand/or a network accessible storage device. The system 700 may include aprogram logic 710 including code 712 that may be loaded into the memory706 and executed by the processor 704 or circuitry 702. In certainembodiments, the program logic 710 including code 712 may be stored inthe storage 708. In certain other embodiments, the program logic 710 maybe implemented in the circuitry 702. Therefore, while FIG. 7 shows theprogram logic 710 separately from the other elements, the program logic710 may be implemented in the memory 706 and/or the circuitry 702.

Certain embodiments may be directed to a method for deploying computinginstruction by a person or automated processing integratingcomputer-readable code into a computing system, wherein the code incombination with the computing system is enabled to perform theoperations of the described embodiments.

The terms “an embodiment”, “embodiment”, “embodiments”, “theembodiment”, “the embodiments”, “one or more embodiments”, “someembodiments”, and “one embodiment” mean “one or more (but not all)embodiments of the present invention(s)” unless expressly specifiedotherwise.

The terms “including”, “comprising”, “having” and variations thereofmean “including but not limited to”, unless expressly specifiedotherwise.

The enumerated listing of items does not imply that any or all of theitems are mutually exclusive, unless expressly specified otherwise.

The terms “a”, “an” and “the” mean “one or more”, unless expresslyspecified otherwise.

Devices that are in communication with each other need not be incontinuous communication with each other, unless expressly specifiedotherwise. In addition, devices that are in communication with eachother may communicate directly or indirectly through one or moreintermediaries.

A description of an embodiment with several components in communicationwith each other does not imply that all such components are required. Onthe contrary a variety of optional components are described toillustrate the wide variety of possible embodiments of the presentinvention.

Further, although process steps, method steps, algorithms or the likemay be described in a sequential order, such processes, methods andalgorithms may be configured to work in alternate orders. In otherwords, any sequence or order of steps that may be described does notnecessarily indicate a requirement that the steps be performed in thatorder. The steps of processes described herein may be performed in anyorder practical. Further, some steps may be performed simultaneously.

When a single device or article is described herein, it will be readilyapparent that more than one device/article (whether or not theycooperate) may be used in place of a single device/article. Similarly,where more than one device or article is described herein (whether ornot they cooperate), it will be readily apparent that a singledevice/article may be used in place of the more than one device orarticle or a different number of devices/articles may be used instead ofthe shown number of devices or programs. The functionality and/or thefeatures of a device may be alternatively embodied by one or more otherdevices which are not explicitly described as having suchfunctionality/features. Thus, other embodiments of the present inventionneed not include the device itself.

At least certain operations that may have been illustrated in thefigures show certain events occurring in a certain order. In alternativeembodiments, certain operations may be performed in a different order,modified or removed. Moreover, steps may be added to the above describedlogic and still conform to the described embodiments. Further,operations described herein may occur sequentially or certain operationsmay be processed in parallel. Yet further, operations may be performedby a single processing unit or by distributed processing units.

The foregoing description of various embodiments of the invention hasbeen presented for the purposes of illustration and description. It isnot intended to be exhaustive or to limit the invention to the preciseform disclosed. Many modifications and variations are possible in lightof the above teaching. It is intended that the scope of the invention belimited not by this detailed description, but rather by the claimsappended hereto. The above specification, examples and data provide acomplete description of the manufacture and use of the composition ofthe invention. Since many embodiments of the invention can be madewithout departing from the spirit and scope of the invention, theinvention resides in the claims hereinafter appended.

What is claimed is:
 1. A method, comprising: receiving, via acomputational device, input data and control data, wherein the controldata includes instructions to modify one or more operations performedduring a runtime execution associated with the input data; processingthe control data to modify the one or more operations during the runtimeexecution associated with the input data; and in response to determiningthat for at least a portion of the input data no corresponding schema toprocess the portion of the input data has been received, wherein theinput data does not refer to a schema for a previous record, and inresponse to determining that the input data cannot be processed withoutgenerating one new schema, generating a new schema to process theportion of the input data for which no corresponding schema has beenreceived, wherein the control data provides a first instruction formodifying a first operation to be performed during the runtimeexecution, and no instructions are provided for modifying a secondoperation to be performed during the runtime execution, the operationsfurther comprising: modifying the first operation in accordance with thefirst instruction during the runtime execution; and performing thesecond operation without any modification during the runtime execution.2. The method of claim 1, wherein the control data includes a schema,the method further comprising: processing the input data in accordancewith the schema provided by the input data.
 3. The method of claim 1,wherein the receiving and the processing is performed by an ExtractTransform Load (ETL) component that executes in the computationaldevice, and wherein the ETL component extracts information from theinput data and the control data, transforms the information inconformance with operational needs, and loads the transformedinformation to generate an output.
 4. The method of claim 1, wherein atleast a plurality of data records in the input data are structuredhierarchically.
 5. The method of claim 1, wherein at least one schemaassociated with the input data changes over time.
 6. The method of claim1, the method further comprising: parsing data records of the input datain accordance at least one schema; and processing the parsed datarecords via an Extract Transform Load (ETL) job that executes in thecomputational device.